Using Analytics to Choose Inventory for a New Season

Making purchasing decisions for a store or retail business is a complicated proposition. The decision-making becomes especially complex when you are trying to determine which products deserve permanent shelf space on your store floor; and which need to be discounted or sent back to the warehouse to make room for new inventory. It can also be difficult to know the answer to sourcing questions such as when to respond to trends, how much to purchase of a specific item and what price-points to sell at for maximum profitability. As a result, an increasing number of retailers are relying on predictive analytics to make more informed purchasing decisions. In fact, according to Martech Advisor, 57 percent of B2B marketers said predictive analytics was their “primary tool” for 2017.

Consider the following to learn more about how predictive analytics are helping companies to maximize sales and to make the most of their inventory budgets.

Determine Top-Performing Categories

Before a retailer can begin using predictive analytics to make better purchasing decisions, they have to determine the top-performing categories in their existing inventory. These can be found by collecting data on factors such including: sales numbers their POS system, consumer engagement with product images in specific categories and high-traffic areas on the company’s website. From here, a retailer can determine which categories are the most profitable, as well as what categories could be expanded to increase future sales.

Forecast Future Seasonal Inventory

Once a retailer knows where to expand their existing inventory, it is time to measure seasonal sales from past years against current industry trends to forecast seasonal sales. This helps determine how large of an order to place for a specific item, as well as where to take a well-calculated risk with a new trend or category. Targeted purchasing recommendations can be derived from this information, so retailers can order only what they need, when they need it – thus boosting seasonal sales and reducing the risk of end-of-the-season discounting.

 Adjust Strategy Where Necessary  

The capabilities of predictive analytics don’t stop once a retailer rolls out their new inventory. Analytics-based software monitors and reports on sales performance, so retailers can keep track of which seasonal inventory categories are the most successful and make modifications to their orders whenever necessary. This means that only the best-selling merchandise gets a place on the show floor. Since NectarOM uses the “Test and Learn” method, we are able to quickly respond to sales activity, so that clients can adapt their purchasing strategy in order to augment ROI.

Keeping Abreast of Trends 

It is essential for retailers to utilize predictive analytics when making seasonal purchasing decisions to remain competitive. In fact, Martech Advisor reports that 82 percent of B2B companies used predictive analytics in last year – and of the companies who did not, 67 percent intend to implement predictive analytics in 2018. It is not only important for retailers to have access to the consumer data, but also to have data-based forecasting software which enables them to quickly respond to industry trends and customer behavior. At NectarOM, we provide clients with software with real-time reporting capabilities that clearly outline actionable recommendations – so they can amplify seasonal sales and adjust to changing consumer preferences.

Using Analytics to Choose Inventory for a New Season

Making purchasing decisions for a store or retail business is a complicated proposition. The decision-making becomes especially complex when you are trying to determine which products deserve permanent shelf space on your store floor; and which need to be discounted or sent back to the warehouse to make room for new inventory. It can also be difficult to know the answer to sourcing questions such as when to respond to trends, how much to purchase of a specific item and what price-points to sell at for maximum profitability. As a result, an increasing number of retailers are relying on predictive analytics to make more informed purchasing decisions. In fact, according to Martech Advisor, 57 percent of B2B marketers said predictive analytics was their “primary tool” for 2017.

Consider the following to learn more about how predictive analytics are helping companies to maximize sales and to make the most of their inventory budgets.

Determine Top-Performing Categories

Before a retailer can begin using predictive analytics to make better purchasing decisions, they have to determine the top-performing categories in their existing inventory. These can be found by collecting data on factors such including: sales numbers their POS system, consumer engagement with product images in specific categories and high-traffic areas on the company’s website. From here, a retailer can determine which categories are the most profitable, as well as what categories could be expanded to increase future sales.

Forecast Future Seasonal Inventory

Once a retailer knows where to expand their existing inventory, it is time to measure seasonal sales from past years against current industry trends to forecast seasonal sales. This helps determine how large of an order to place for a specific item, as well as where to take a well-calculated risk with a new trend or category. Targeted purchasing recommendations can be derived from this information, so retailers can order only what they need, when they need it – thus boosting seasonal sales and reducing the risk of end-of-the-season discounting.

Adjust Strategy Where Necessary  

The capabilities of predictive analytics don’t stop once a retailer rolls out their new inventory. Analytics-based software monitors and reports on sales performance, so retailers can keep track of which seasonal inventory categories are the most successful and make modifications to their orders whenever necessary. This means that only the best-selling merchandise gets a place on the show floor. Since NectarOM uses the “Test and Learn” method, we are able to quickly respond to sales activity, so that clients can adapt their purchasing strategy in order to augment ROI.

Keeping Abreast of Trends

It is essential for retailers to utilize predictive analytics when making seasonal purchasing decisions to remain competitive. In fact, Martech Advisor reports that 82 percent of B2B companies used predictive analytics in last year – and of the companies who did not, 67 percent intend to implement predictive analytics in 2018. It is not only important for retailers to have access to the consumer data, but also to have data-based forecasting software which enables them to quickly respond to industry trends and customer behavior. At NectarOM, we provide clients with software with real-time reporting capabilities that clearly outline actionable recommendations – so they can amplify seasonal sales and adjust to changing consumer preferences.

Three Reasons Why Email Marketing Really Works

Benefits of Email Marketing

In a world where social media, blogging, and SEO take precedence, email seems like it would be on its way out the door. However, with the business world obsessed with acquiring consumer data, email marketing is not only useful but essential to companies.

Email marketing is one of the most effective and reliable channels for marketers to interact with customers. Here are three reasons why email marketing really works.

1.Easy Way to Reach Mobile Customers

Email marketing is an easy way to reach consumers on mobile without investing in new technology or software. Email channels already exist and are a traditional medium of connection, making it simple to reach consumers. According to a report by Pew Research Center, 52% of cellphone users in the U.S. access their emails via mobile phones. With many consumers constantly on the go, email marketing offers companies a way to send a greater volume of content to consumers in a quick and efficient manner.

Email is also accessible on devices other than mobile phones. According to a study done by Forrester Research, consumers opened 42% of retailers’ emails on smartphones and 17% on tablets. Essentially, nearly 60% of email marketing messages also double as mobile marketing messages. This versatility puts email at an advantage in comparison to text messages and SMS messaging. Consumers are more inclined to open email messages because emails are more accessible. Texting, on the other hand, is only available on mobile devices. Email is also free for the consumer and company while texting risks the chance of an incurred charge on the customer’s end. This diminishes the satisfaction of customer experience and can drive customers away. Also, email marketing is an easier access point for consumers and conveys more content that is useful to consumers.

2. Email is a Transactional Medium

Consumers see emails as a way to get offers, coupons, promotions, and in-stores sales. Email marketing deals drive in-store sales, making product emails key to getting consumers to engage with a product. A study performed by Nielsen found that 27% of online shoppers subscribe to emails in order to save money. 64% of consumers have printed out coupons found on email marketing campaigns.

Since customers expect to see offers and promotions in product emails, they are more likely to be in a buying state of mind. In turn, this can turn into increased revenue opportunity for companies. E-coupons are becoming a huge business with the growth of online sales, and email marketing is at the heart of it. Email marketing reaches out to online bargain hunters and provides consumers with a way to save online and in store. The transactional framework that email marketing provides also allows companies to personalize more toward consumers, engaging them more and further increasing sales opportunities.  

3. Tells You What Works

Email marketing allows companies to see what works and what doesn’t. The data obtained from email marketing provides metrics to see how emails are performing and what companies can do to improve email strategies. These insights allow companies to market their products smarter and better. Learning what works because of email marketing also gives companies a better understanding of the needs, interests, and desires of the consumer base. Companies can see the clickthrough rate of an email, which can then provide data as to how shoppers interact with the online shopping platform. Companies use the information provided by email marketing to not only cater to what consumers are looking for, but to better improve the interaction between consumer and company. By using email marketing, companies can track customer activity and better serve their interests.

Some say email marketing is dead. However, email marketing works. It keeps customers engaged and opens channels of communication between the company and its customers. With email marketing, companies can be in the right place at the right time.

Engaging High-Value Customers for High-Value Results

Many companies are shifting their focus to engage customers with higher value and profitability. The goal of engaging high-value customers (HVCs) is to nurture them into becoming loyal power shoppers. Increasing loyalty to a brand this way ensures retention and lifetime value of customers.

HVCs drive a significant portion of a company’s revenues. These customers are not only intensely loyal to a brand, but help promote the brand and its influence as well. Engaging and satisfying these high-value customers will put a company on a path toward greater success.

What Is a High-Value Customer?

Confusing high volume and high-value customers can be easy. However, high volume customers and high-value customers are two different target markets.

High volume customers are those who interact with a brand frequently. Although they may engage with the brand often, it doesn’t necessarily mean that these customers are the most valuable. Often with high volume customers, a brand will see a surge in activity for short periods of time. However, once the excitement fades, so does customer engagement.

High-value customers are those who buy for a reason. These customers look at products, services, and brands as a way to meet a need and satisfy a drive such as status, health or lifestyle. HVCs are customers who are loyal to a brand or company, even in times of financial duress. They will return to a brand and product even when a cheaper alternative is available. For HVCs, the cost is not a priority, and are more focused on having their unique needs addressed. HVCs are also brand promoters and influencers. These are the customers who will share the brand within their social networks.

Focusing specifically on high VALUE customers reflects an understanding of the power that these consumers have. Identifying who the high value customers are and tailoring marketing schemes to satiate these consumers, keeps them happy and ensures the brands’ profit margins.

  1. Evolve With Customers

Customer habits change and evolve. In turn, the way consumers interact with brands has evolved as well. Instead of fighting this evolution, brands should adapt and keep up with their customers. Part of this evolution includes the introduction of new goods and services and outlets, like online shopping. This development means customers are interested in a wide variety of items at all times. A shift towards items outside a consumer’s regular purchase pattern can indicate consumers are turning into HVCs. Dramatic changes in how customers buy items and spend money can also indicate greater trust and loyalty with a brand. Once the customer has extended the olive branch toward a brand, it is very likely they will shift into the high-value customer category.

  1. Pay Attention

The data provided by a customer’s recent activity can predict if a customer is high value or becoming high value. Data points such as high clickthrough rate, frequent site visits, and large purchases can indicate a customer as a high-value customer. One way to monitor customer involvement and identify high-value customers is through a  triggered marketing campaign. Triggered marketing includes a continuous stream of messages sent to customers based on their shopping activity, browsing history, purchases, etc. Triggered marketing indicates to customers that a brand knows its customers.

  1. Loyalty Rewards

Loyalty programs are teeming with information about members. Everything from brand preferences and item category to price sensitivity can be found in loyalty member data. Harnessing loyalty data helps brands personalize more towards HVCs. Knowing where, when, why, and how customers engage with a brand, can empower companies to create personalized experiences across multiple channels.

Loyalty programs also remove the barrier between customers and their next purchase. These loyalty programs make customers feel like “power users.” Their actions directly correlate to the experience found with a brand and company.

High-value customers make up the untapped bread and butter for many businesses. Understanding the behavior patterns of high-value customers enables brands to engage and target this niche group of customers. Providing high-value customers with the attention they desire keeps them engaged with the brand and propels companies to further success.

 

Outsmart the Smartphone: Expert Insights into Mobile Marketing

Marketers know mobile marketing is a critical component of any marketing strategy. Consumers cannot live without their smartphone and mobile device’s have become an integral part of consumer’s daily life.

 

Despite knowing the inherent impact of mobile, many brands are struggling to create and implement an effective mobile strategy. Yesterday’s American Marketing Association (AMA) meeting helped marketers better understand how to outsmart the smartphone and optimize their mobile marketing strategy.

 

Experts Scott Talbott from Verve Mobile, John Nosal from Advice Local, Abhi Vyas from Dex Media, and Bryon Morrison from NectarOM, sat down and shared how your brand can outsmart the smartphone.

 

Dallas AMA Mobile Marketing Panel

 

Here are a few highlights from the panel discussion.

 

Consider the Omni Channel Experience  

In addition to the 40 or so apps on your phone you also have the option to do email, send SMS, browse the web, post on social media, and receive push notifications. Smartphones have put 6 channels into one device along with more than 100 sensors, making it more important for marketers to think about the omni channel experience the device creates. Traditionally brands have siloed channels, creating a disconnected experience for the customer. Mobile is forcing marketers to break down silos and unify their efforts. Bryon Morrison suggested the consumer needs to be the center of the customer journey, not the channels. He continued, “If you understand the individual and their motivations then the mobile device is the most important marketing tool, because it packages all the channels in one device along with movement.

 

Target the Right Person at the Right Place and at the Right Time with the Right Message

From a location perspective mobile unlocks an interesting opportunity for marketers: location based marketing.  Customers are starting to expect brands to tailor content to their location, and are more likely to convert when content is customized to their location. Brands leading with location by utilizing location based advertising or managing their local presence will be more likely to convert mobile customers.  John Nosal believed that brands who focus on the mobile experience will win more customers.

 

“61% of smartphone users are more likely to buy from mobile sites and apps that customize information to their location.”

 

Get in the Game

When asked who is doing a great job in mobile, Morrison replied, “The ones in the game that are testing and failing fast.” He cited specific examples of early innovators that are now experiencing great success with mobile – eBay and their multi-app strategy were the first to post a billion in mobile sales; Walgreens gets 6x more revenue from customers that download their app; Walmart attained a 2% increase in conversions by shaving 4.3 seconds off their page download time.

Nosal responded that Starbucks was a leader in the mobile experience citing the ability to order and pay for coffee through their app.  He also mentioned grocery stores like Tom Thumb (parent company, Albertsons) are leading the way, mentioning ability to build grocery lists through scanning barcodes with the app and use of push notifications to notify consumers of deals.

 

Know the Metrics that Matter

Don’t get caught up in the funnel metrics.  Keep it simple and make sure that your KPIs link to mobile moments that matter like conversions and sales. Scott Talbott gave an example of automobile marketers getting too caught up in desktop web funnel metrics while missing out on the opportunity to reach prospects while they are physically standing on a dealership lot. Morrison also shared an example of a client that spent an immense amount of energy on app optimization, as opposed to growing their SMS channel which was delivering in-store mobile coupon conversions between 25%-45%.

 

Get to Know Your Customers   

Brands know it is important for them to understand their customer and Abhi Vyas mentioned 81% of them think they are doing a good job. However, only 37% of customers think their favorite retailer understands them. The panel agreed this was a function of marketing departments, as opposed to mobile marketing. As an example, Morrison mentioned that marketing departments are often set up to launch and manage channels which is time consuming and laborious. That creates silos and makes cross channel marketing a challenge.  If organizations focused on profiles and used a personalization platform then their ability to integrate a new channel would be much faster, easier and cost effective. That approach would also allow a brand to innovate faster which is currently being outpaced by consumer sophistication levels and expectations.

Talbott proposed one way companies could better market is by focusing on context, stating that “content is now secondary to context.” He also mentioned that mobile location matched against 1-to-1 knowledge of a customer is the best way a marketer can get to an understanding of intent.

 

If you are interested in learning how you can better deliver the right message, at the right time, to the right person let us know and schedule a demo to see the NectarSuite in action.

The Business Imperative: Personalization

This Wednesday, the DFW-Retail Executives Association ended its season on a timely topic for retailers: Personalization.  If you missed out on this panel or are one of the 77 percent of companies saying, “In 2016 we need to be doing personalization,” have no fear we have the panel highlights for you.

Cover Photo Amrit Speaking at REA Personalization Panel
DFW REA Personalization Panel

The panel consisted of three experts,

  • Jeff Rosenfeld-Vice President of Customer Insights & Analytics at The Neiman Marcus Group
  •  Veeral Rathod- Chief Executive Officer & Co-Founder at J. Hilburn Clothiers
  • And NectarOM’s very own Chief Executive Officer & Founder Amrit Kirpalani.

Panel Moderator Steve Dennis kicked off the panel discussion setting the stage for why personalization is quickly becoming a business imperative.  Explaining that personalization is  “an imperative because the battle has shifted from market share to share of attention- and it’s increasingly difficult to be the signal amidst the noise.”

The rest of the discussion focused on how personalization is changing their marketing efforts, what challenges they faced when launching their personalization efforts, how it is changing marketing, and finally discussed how other companies could successfully launch their own personalization efforts.

Here are a few of our favorite topics from the panel,

Test and Learn

Don’t start off trying to personalize every message coming from every channel.  Amrit suggested that the clients with the most success started off small.  Start off testing a few channels and messages at a time, learn what worked and then test some more.

Be Prepared to Think About Marketing Differently

Personalization fundamentally changes how marketing has been done for years. Instead of a one size fits all strategy, personalization shifts the focus to marketing on a one-to-one level.  Jeff and Amrit agreed that culture change was one of the biggest challenges when companies started discussing personalization.

Not a One Size Fits All Solution.

Take the time to figure out how personalization fits into your company’s structure and into what your customers want.   The Neiman Marcus Group and  J. Hilburn Clothiers both used personalization in the retail space, however they each had a unique approach that fit their customer and business model’s needs.

Have the right partners in place

Not everyone can afford to have a team of data scientists creating custom algorithms.  However, personalization is something that is becoming more realistic for companies of all shapes and sizes to start adding to their marketing efforts. All you need to do is find the right partner.

If you are interested in learning more about sending tailored messages to your customers in real-time across all your owned channels let us know and schedule a demo to see the NectarSuite in action.

When Big Data Analytics Hurts Innovation

Making use of Big Data is a staple of every digital marketer’s playbook, especially those in the retail sector who will use it to measure such things as transaction and customer loyalty. There is a lot of potential to be found in Big Data analytics, but it’s lost when retailers grow too comfortable with a “proven” approach and fail to keep testing and discovering new viable marketing strategies. Ultimately, realizing the limits of Big Data analytics and becoming comfortable with experimentation is the key to making sure your business stays in touch with the demands of its environment and its customers.

Analytics are Impressive, but Incomplete

Current trade promotion optimization (TPO) solutions simply weren’t designed to extract signal from the large volume of noisy data that modern retailers generate, and analytics is still unable to specifically measure the effect of qualitative factors like ad design, layout, and wording on ROI. This means that, for better or worse, the current limitations of our technology mean that Big Data can only give us a partial look at what worked and what did not.

Don’t get me wrong. Data analytics provides marketers with an incredible degree of insight, but we must remember to use it as a tool with defined goals and a good understanding of what it can and cannot accomplish.

For instance, analytics is much better at explaining the past than predicting the future. This means that you can’t predict with certainty the effect that a certain kind of discount, pricing structure, or cross-merchandising tactic will play out: you need to run an experiment. This can be scary, but an unwillingness to try new things could leave your business wading in the shallow end of success, perhaps losing very little but not making much either.

Offer Innovation: A Better Way

As a rule, the best way to experiment in this field is to maximize your exposure to positive (beneficial) risks while minimizing your exposure to negative risk. The best way to do so in the omnichannel age is to experiment with offer innovation, a series of micro-tests that you can use to analyze the small-scale performance of diverse offers and messages across channels. Instead of shifting your entire marketing campaign in one great, lurching motion, you’ll be testing many ideas at once and keeping an eye on any promising developments without risking the bulk of your business. The gamble you’re taking is absorbing little failures (i.e., a particular method falls flat) in hopes that you’ll stumble upon a new, reliable way to connect with a certain kind of customer.

Ironically, realizing the limitations of data analytics will help you make better decisions and make more calculated risks. Don’t be afraid to make small mistakes, especially when there’s a large potential payoff at the end.

Clickstream Data in an Automated World

Clickstream technology is vital to understanding customers in any web associated business. The ability to track customer activity across digital fronts allows analysts and marketing teams to easily optimize UX, enrich their CRM, and enhance personalization. One of the key success factors for personalization is segmentation, and installing a clickstream tool can help build customer profiles to power automation engines and personalization.

Although clickstream is most intuitive for website use, it also provides value for other channels. For instance, basic analytics tools and most email services can show you the click-through rate, but using a clickstream will allow you to track which links were clicked and also track through the link onto a website to continue building the customer pathway as a prospect navigates through your digital world.

Marketing automation tools like nectarOM can help make the process of pulling in clickstream data, segmenting customers, and executing campaigns easier, but understanding how clickstream data can build or validate customer personas and profile types builds the base for more advanced personalization.

Analysis of historical data, like # of clicks on different assets, first session time, page view time, # of site visits, total session time, and tons of other data points that can help build understanding about an individual’s habits and personality type. Historical data can even be mapped to show progression of the customer through time, and analysis can see how each data point has changed over the lifecycle of an individual. With enough time, an automation tool, and planning, these data points can easily be imported into a CRM tool to enrich the existing customer information and fed into a marketing automation platform

Historical data about an individual customer can provide insights, but making clickstream data actionable enough requires laying out significant linkage between clickstream behavioral triggers and executed marketing engagement.

A marketing automation tool will make the act of ingesting and digesting new data points, and sending messages or content to customers much easier, but just like manual lists and campaigns, marketers will face challenges in describing what should prompt a marketing message or a change in content.

Things to keep in mind:

clickstream-customer-data

1. What describes a customer behavior change?

Many automation tools have predetermined algorithms that measure changes in quantitative history to optimize messaging, but each business is different.

2. Who are your buyer personas?

If you already have previously validated segments, how should they mesh with new clickstream data being pulled in? How is your clickstream data meshing with other customer data points from social, email, POS, and other sources.

3. What is your content?

This is often the most difficult and overlooked part in the personalization and automation evolution. Because sending relevant, personalized messages is important, how do you ensure that variants of content are enough, but not too much for your team to handle? The more personalized your marketing becomes, the more complex content to behavior linking will be. Marketer accessible data like like names, location, etc is much easier to personalize than things like design, copy, and other labor heavy work.

Clickstream is powerful, and it works, but utilization of the relatively easy to install tool requires a lot of thought into how it will enrich customer data, power automation and personalization, and ultimately increase marketing ROI. What are your challenges with clickstream data?

Big Data Analytics: The Key to Unlocking Business Potential

Using Big Data to Drive RevenuePositive Results From the Smart Use of Big Data Analytics (3rd in a Series)

I recently spoke with several high level marketing executives about the near-ubiquitous topic, BIG DATA. The executives included Paul Golden, ex-CMO of Samsung Mobile, Barry Judge (ex-CMO of Best Buy, current CMO of LivingSocial, and Brad Todd, (Principal at The Richards Group). In this third installment, we review some of the results these executives experienced.  Big data analytics was the key in making the information they had actionable to drive customer value.

Brad Todd has helped clients use their data in very sophisticated ways, by applying rigorous big data analytics.  A home improvement retailer, for instance, has used information from their customers’ do-it-yourself projects to engage in helpful conversations with their customers. This type of engagement not only makes the customer feel valued, but very often leads to follow-on projects and increased customer loyalty.  For instance, if a customer has planned a deck using online tools, the retailer can follow up with them at predicted intervals with suggestions and relevant offers to improve the likelihood of purchase.

The Richards Group also helps their clients integrate their marketing data and then apply big data analytics, with the objective of personalizing customer communications.  They have seen improvements of 20% on average when website, email and remarketing channels are personalized to customers.  The results are even greater—about 25% if cross-channel personalization occurs.

At Samsung Mobile, Paul Golden used longitudinal brand preference data to prioritize markets for their marketing efforts.  He and his team tailored brand messages and tactics for eight key markets to improve brand preference versus a key competitor.  The result was a swing from a relative score of -6 to +2 in overall brand preference, despite only focusing on eight key markets.  Big data analytics allowed Samsung Mobile to cost-effectively determine which markets would swing the entire country’s brand preference score in their favor.

While CMO of Best Buy, Barry Judge and his team applied big data analytics to vast amounts of customer information to zero in on their highest value customers.  They then tailored all their marketing to best serve those customers and increase their engagement.  Knowing their customers and what their shopping habits allowed Best Buy to offer the most relevant products and offers to promote via email and direct mail.  By focusing on their most loyal customers, they grew their loyalty even more and increased their share of wallet with these customers.

Big data can be a big deal in driving results for brands if used to improve customer interactions.  Set objectives, determine what data is needed to achieve those objectives, compile and analyze the data, then translate it into something valuable for your customers.

Want to learn more about how to use big data analytics to improve business results? Click here.

And please feel free to leave any comments or questions below.

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How Marketing Executives Use Big Data: All Types of Data Sets At the Right Time

Data Management Platform

I recently spoke with several high level marketing executives about the near-ubiquitous topic, BIG DATA. The executives included Paul Golden, ex-CMO of Samsung Mobile, Barry Judge (ex-CMO of Best Buy, current CMO of LivingSocial, and Brad Todd, (Principal at The Richards Group). Each of the executives with whom we spoke had used all types of data sets in different ways.  Depending on the need of the business, they called on different types of data sets to achieve their purpose.  Given their focus on marketing, the types of data sets tended to be tied to customers.

As a principal at The Richards Group since its inception, Brad Todd has seen a lot of changes in how advertising clients have used data. He recalls the proliferation of data from the introduction and use of loyalty cards at grocery stores. Although grocers captured vast amounts of information about their customers—what they bought, how often they purchased, how they paid—very little of that data was used to improve the customer relationship.  The data was primarily used for managing inventory and shelf space.  Arguably, having fully-stocked shelves does help the customer experience, but the primary use of the data was to improve the bottom line.  Today, grocers and their CPG partners have begun to combine many types of data sets for more targeted marketing.

While CMO of Best Buy, Barry Judge and his team used different types of data sets–purchase history, clickstream analysis, email interactions, demographics and psychographics–to identify and deliver relevant product offerings to their customers.  However, integrating newer analytics tools into legacy systems posed roadblocks.  And incorporating data from the physical store, in order to have a truly holistic picture of each customer, was very difficult.

At Barry’s current company, Living Social, the relative newness of the company and the lack of a physical channel makes it easier to combine data.  They have used customer information to prioritize offers according to each customer’s purchase history and click behavior, thus making the customer experience much more relevant.

Paul Golden, while he was CMO at Samsung Mobile, used big data to improve the brand preference score for Samsung’s mobile phones.  Applying analytics to their big data allowed Paul and his team to identify key markets and determine the most relevant messages for those key markets.

Once you get past the hype and noise, big data can be very useful.  The important thing is to clearly define your objectives and use the data to meet those objectives.

Want to learn more about how to connect different types of data sets? Click here.

And please feel free to leave any comments or questions below.

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